Strategic Conversations: LLMs Argumentation and User Perception in Movie Recommendation Dialogues

This study investigates the persuasive and argumentative behaviors of two LLM-based chatbots, ChatGPT and Gemini, within the context of movie recommendation dialogues. Drawing on insights from argumentation-based dialogue and anthropomorphism research, we introduce a fine-grained annotation scheme to analyze chatbot strategies across dialogue phases. Through both linguistic analysis and user evaluation via ResQue and Godspeed questionnaires, we assess the systems’ recommendation quality, perceived human-likeness, and strategic variation. Our findings reveal distinct conversational patterns.